podkeet 1.1.1

Download YouTube audio as MP3 and transcribe with Parakeet-MLX (Apple Silicon/MLX)

podkeet

Download a YouTube video's audio as MP3 with yt-dlp and transcribe it using Parakeet-MLX (MLX on Apple Silicon).

Requirements

• macOS on Apple Silicon (M1/M2/M3/M4)
• Python >= 3.13
• ffmpeg (for yt-dlp post-processing)
  • Install on macOS: brew install ffmpeg

Parakeet-MLX is installed as a dependency and will use MLX (Metal) on Apple Silicon when device=auto.

Quick start

Run directly with uvx (no virtualenv needed):

uvx podkeet transcribe "https://www.youtube.com/watch?v=dQw4w9WgXcQ" --out-dir ./outputs

Note: The first run will install the podkeet CLI automatically. If you prefer a persistent install:

uvx pip install -U podkeet

Or, if you prefer working in a virtual environment:

uv venv --python 3.13
uv sync --extra dev
podkeet transcribe "https://www.youtube.com/watch?v=dQw4w9WgXcQ" --out-dir ./outputs

This will:

• Check for ffmpeg and instruct you to install it if missing.
• Download the best audio stream and convert it to MP3.
• Transcribe the MP3 with Parakeet-MLX, saving a transcript next to the audio (and in --out-dir).

Installation (PyPI)

Once released on PyPI, you can install directly:

uvx pip install -U podkeet

CLI reference

• podkeet download URL --out-dir PATH [--no-timing]
• podkeet transcribe URL_OR_FILE --out-dir PATH [--keep-audio] [--language auto|en|…] [--model NAME] [--format txt|srt|vtt|json] [--device auto|mps|cpu] [--no-timing] [--version]

Notes:

• If ffmpeg is missing, a clear message explains how to install it.
• The first transcription may download Parakeet-MLX models; subsequent runs use the local cache.
• On Apple Silicon, device=auto prefers MLX (mps) and falls back to CPU if needed.
• Timing: The CLI shows elapsed time for download and transcription; hide with --no-timing.
• JSON: When --format json is used, the CLI prints a compact JSON summary to stdout (suitable for automation).

Robustness

• Filenames with special characters: We detect the actual file written by yt-dlp instead of guessing by title, avoiding path mismatches.
• Large files / memory: If a full-file transcription hits a Metal/MLX memory error, the tool automatically falls back to chunked transcription (~10-minute segments) and merges results with correct timestamps.
• Network hiccups: The downloader uses retries, socket timeouts, and exponential backoff to handle transient network failures.

Examples

# Download only
podkeet download "https://www.youtube.com/watch?v=8P7v1lgl-1s" --out-dir ./podcasts

# Transcribe from URL with a specific start (yt-dlp handles t=)
podkeet transcribe "https://www.youtube.com/watch?v=8P7v1lgl-1s&t=121s" --out-dir ./podcasts

# Transcribe a local file to SRT
podkeet transcribe ./podcasts/example.mp3 --out-dir ./podcasts --format srt

# JSON summary output (includes timings):
podkeet transcribe "https://www.youtube.com/watch?v=dQw4w9WgXcQ" --format json | jq

Development

Install dev extras and set up the environment:

uv venv --python 3.13
uv sync --extra dev

Format with Ruff:

uvx ruff format

Lint with Ruff:

uvx ruff check
uvx ruff check --fix

Type-check with Ty (pre-release):

uvx ty check

Run tests:

uv run pytest -q

Build package (sdist + wheel):

uvx --from build pyproject-build
ls dist/

CI/CD

• CI (lint, type, tests, build) runs on pushes and PRs.
• Releases are automated:
  • Conventional Commits drive version bumps and CHANGELOG.md via Python Semantic Release.
  • A tag vX.Y.Z is created on main.
  • The Release workflow builds and publishes to PyPI using OIDC (Trusted Publishing).

Commit message hints (Conventional Commits):

• feat: … → minor version bump
• fix: … → patch version bump
• feat!: … or footer BREAKING CHANGE: → major version bump

Troubleshooting

• ffmpeg not found: brew install ffmpeg (then re-run).
• MLX out-of-memory: The tool will switch to chunked transcription automatically; if still failing, try a smaller model.
• Network or YouTube rate limiting: The downloader retries with backoff; re-run later if persistent.

License

MIT